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Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover photo and the text in the title and description could be combined in a fusion classifier to better predict the crowdfunding campaign’s success. In this work, we focus on the performance of the crowdfunding campaigns on GoFundMe across a wide variety of funding categories. We analyze the attributes available at the launch of the campaign and identify attributes that are important for each category of the campaigns. Furthermore, we develop a fusion classifier based on the random forest that significantly improves the prediction result, thus suggesting effective ways to make a campaign successful.


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What Contributes to a Crowdfunding Campaign’s Success? Evidence and Analyses from GoFundMe Data

Show Author's information Xupin Zhang1Hanjia Lyu2Jiebo Luo3( )
Warner School of Education and Human Development, University of Rochester, Rochester, NY 14627, USA
Goergen Institute for Data Science, University of Rochester, Rochester, NY 14627, USA
Department of Computer Science, University of Rochester, Rochester, NY 14627, USA

Abstract

Researchers have attempted to measure the success of crowdfunding campaigns using a variety of determinants, such as the descriptions of the crowdfunding campaigns, the amount of funding goals, and crowdfunding project characteristics. Although many successful determinants have been reported in the literature, it remains unclear whether the cover photo and the text in the title and description could be combined in a fusion classifier to better predict the crowdfunding campaign’s success. In this work, we focus on the performance of the crowdfunding campaigns on GoFundMe across a wide variety of funding categories. We analyze the attributes available at the launch of the campaign and identify attributes that are important for each category of the campaigns. Furthermore, we develop a fusion classifier based on the random forest that significantly improves the prediction result, thus suggesting effective ways to make a campaign successful.

Keywords:

crowdfunding, image-text fusion, GoFundMe
Received: 26 March 2021 Revised: 31 May 2021 Accepted: 28 June 2021 Published: 23 August 2021 Issue date: June 2021
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Publication history
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Publication history

Received: 26 March 2021
Revised: 31 May 2021
Accepted: 28 June 2021
Published: 23 August 2021
Issue date: June 2021

Rights and permissions

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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